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采用人工神经网络方法建立了Ti-10V-2Fe-3Al合金机械性能预测的神经网络模型。模型的输入参数包括变形温度、变形程度、固溶温度、时效温度等热加工工艺参数和热处理制度。模型的输出为钛合金最重要的5个机械性能指标,即抗拉强度、屈服强度、延伸率、断面收缩率和断裂韧性。与传统回归拟合公式相比,该模型具有容错性好、通用性强等优点。该模型可以预测Ti-10V-2Fe-3Al合金在不同热加工工艺参数和热处理制度下的机械性能,也可以用于优化热加工参数和热处理制度。
A neural network model of mechanical properties prediction of Ti-10V-2Fe-3Al alloy was established by artificial neural network. The model input parameters include deformation temperature, degree of deformation, solution temperature, aging temperature and other thermal processing parameters and heat treatment system. The output of the model for the titanium alloy is the most important five mechanical properties, namely, tensile strength, yield strength, elongation, reduction of area and fracture toughness. Compared with the traditional regression fitting formula, the model has the advantages of good fault tolerance and versatility. The model can predict the mechanical properties of Ti-10V-2Fe-3Al alloy under different thermal processing parameters and heat treatment system, and can also be used to optimize the thermal processing parameters and heat treatment system.